Neurons do math to distinguish predictions from reality

WASHINGTON, DC - Neir Eshel, a neuropsychiatry research pioneer who uncovered novel insights about how dopamine neurons are wired to help us navigate the consequences of our choices, has been named the 2016 Grand Prize winner of the Science & SciLifeLab Prize for Young Scientists. The prize recognizes promising early-career scientists who conduct groundbreaking life-science research and includes a grand-prize award of US $30,000, supported by Science for Life Laboratory, a coordinated effort among four universities in Sweden and the journal Science, which is published by AAAS, the nonprofit science society.

Dr. Eshel and colleagues at Harvard University expanded on the basic finding that we learn by comparing predictions to reality, then updating those predictions accordingly, using a simple mechanism evolved by the brain. Dopamine neurons are key players in this process, with a unique ability to calculate prediction error, or the difference between actual and predicted reward.

Despite extensive studies exploring the effect this type of reinforcement has on behavior, little is known about how dopamine neurons actually calculate prediction error. Interested in how nerve cells processed predictions related to decision making, Eshel, now a psychiatry resident at Stanford University, combined optogenetics (harnessing light to control cells like neurons) with classical recording techniques, carefully-designed behavioral tasks and computational analysis to investigate further.

"Many researchers have used optogenetics alone to explore how behavior changes when a subset of neurons is activated or inhibited. While these experiments are important, the results can be hard to interpret, because it is unclear if the manipulated neurons ever respond this way during natural behaviors," said Eshel. "To truly understand how circuits function during behavior, a combination of methods is needed," he added.

He zeroed in on the small portion of the brain called the ventral tegmental area (VTA), where dopamine is produced. This same region of the brain also contains inhibitory GABA neurons, which signal how much reward to expect. Intrigued by the possibility that dopamine neurons could use the GABA expectation signal to calculate prediction error, his team selectively infused VTA GABA neurons with a light-sensitive protein to control their activity. The scientists recorded GABA and dopamine neuron activity as the animals performed easy learning tasks.

Following VTA GABA neuron stimulation, the mice's dopamine neurons responded to unanticipated rewards as if they were anticipated. Conversely, when the VTA GABA neurons were inhibited, dopamine neurons responded to expected rewards, much like they were unexpected. "If we activated the VTA GABA neurons simultaneously on both sides of the brain, we even changed the animals' behavior," Eshel noted. After training mice to await a certain size of reward, the researchers artificially increased the expectation level by stimulating VTA GABA neurons during the anticipation period, maintaining the same reward amount. Following several trials where expectation exceeded reality, the disappointed rodents stopped anticipating a reward.

Eshel's work revealed that individual dopamine neurons responded in a remarkably similar fashion, and were essentially indistinguishable from one another. "This uniformity greatly simplifies information coding, allowing prediction errors to be broadcasted robustly and coherently throughout the brain - ensuring that the rest of the brain can decipher the message loud and clear," said Eshel.

Importantly, Eshel also found that dopamine neurons take a simple mathematical approach to prediction errors - by subtracting expectation from actual reward. "Subtraction like this is rare to find in the brain, but it's ideally suited for this purpose, allowing for consistent and precise calculations," said Eshel.

In Eshel's grand-prize winning essay, "Trial and error" which will appear in the 2 December 2016 issue of Science, he highlights how his team's research methods allowed them to pinpoint the origin of prediction signals. While these GABA neurons were previously difficult to analyze, they may now be studied in greater detail, using Eshel's approach.

"As always, we are delighted by the high level of accomplishment that we see in all the Science & SciLifeLab Prize applicants. This year stands out for the ability shown by the winners to apply current technologies in new ways, to answer fundamental questions and provide potentially life-saving insights," said Barbara Jasny, deputy editor of Science.

Eshel is excited about the possible implications for his patients, particularly those affected by addiction, a disease he sees every day in the emergency rooms and hospital wards. "Addiction has been conceptualized as a disorder in which the dopamine prediction error system is hijacked, so that drugs of abuse always appear better than expected," said Eshel. "Now that we know more about how dopamine neurons calculate prediction error, we can better target our therapies."

Eshel will receive the award for his research in the field of cell and molecular biology in Stockholm, Sweden, on Friday, 9 December, during an award ceremony and dinner at the Grand Hôtel in the Hall of Mirrors, which hosted the first Nobel Prize ceremony in 1901.

"SciLifeLab is very happy to note that there were more applications for the prize in 2016 compared to previous years and also that the geographical spread was bigger," said Lena Claesson-Welsh, Co-Director of SciLifeLab. "The prize is clearly becoming established as a very prestigious award for young scientists. We look forward very much to hosting the winners of 2016 and welcome them to Sweden to receive the awards for their great achievements."

The Science & SciLifeLab Prize for Young Scientists is an annual prize aimed at rewarding young scientists at an early stage of their careers. The categories for this annual award are Cell and Molecular Biology, Ecology and Environment, Genomics and Proteomics, and Translational Medicine.

Applicants for the 2016 Science & SciLifeLab Prize for Young Scientists submitted a 1000-word essay that was judged by an independent editorial team organized by the journal Science. Its content was evaluated on the quality of research and the applicants' ability to articulate how their work would contribute to the scientific field.

Neir Eshel: For his essay, "Trial and error." Eshel is a psychiatry resident at Stanford University, pursuing a career at the interface of research and clinical practice. He is interested in how we learn about rewards and punishments, how we make decisions based on this knowledge, and how these systems break down in neuropsychiatric disease. He has conducted research at the National Institutes of Health, Princeton University, the World Health Organization, University College London, and Harvard University. Outside the lab and clinic, Neir plays clarinet in chamber groups and orchestras and is a passionate advocate for LGBT health equality.

2016 Runners-up:

David Seekell: For his essay on the topic of ecology and environment, "Passing the point of no return." Seekell is an environmental scientist based in Sweden. He holds a Bachelor of Science in Natural Resources from the University of Vermont, and a Ph.D. in Environmental Sciences from the University of Virginia. In his PhD research, Seekell developed statistics to provide early warning that an ecosystem is passing a tipping point, and is about to undergo a regime change. He is currently an Assistant Professor of Ecology in the Department of Ecology and Environmental Science at Umeå University. In 2015 he became a Wallenberg Academy Fellow, and in 2016, he received a Science for Solutions Award from the American Geophysical Union.

Sam Behjati: For his essay on the topic of genomics and proteomics, "Retracing embryological fate." Originally from Germany, Behjati read medicine at Oxford University and pursued post-graduate clinical training in London, UK. Funded by the Wellcome Trust, he joined the Cancer Genome Project of the Sanger Institute (UK) for doctoral research. Using a "mutational postcode" that cells acquire as they divide, Behjati has shown that it is feasible to reconstruct early developmental processes in the adult mouse. Building on ideas developed during his PhD, he now aims to define the embryonic origin and fate of childhood cancer cells.

Canan Dagdeviren: For her essay on the topic of translational medicine, "The future of bionic dynamos." Dagdeviren was born in 1985 in Istanbul, Turkey. As a Fulbright Doctoral Fellow, she received her Ph.D. degree in Material Science and Engineering at the University of Illinois at Urbana-Champaign. Dagdeviren developed a conformable, piezoelectric energy harvester that converts mechanical energy from internal organ movements into electric energy to power medical devices. It is soft and flexible, and conforms to the heart as well as other soft tissues. This technology could extend the battery life of implanted electronics or eliminate the need of battery replacement, sparing patients from repeated operations and the risk of surgical complications. Beginning in January 2017, she will assume the role of Assistant Professor at the MIT Media Lab, where she will direct the Conformable Decoders research group.

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About SciLifeLab

SciLifeLab, Science for Life Laboratory, is a Swedish national center for molecular biosciences, with the mission to develop, use and provide advanced technologies for applications in health and environmental research. The center was established in 2010 and became a national resource in 2013, making technologies and expertise available to researchers in all of Sweden and beyond. Today the center comprises more than 1 200 researchers and personnel. We offer a cross-disciplinary research setting that interacts with healthcare, authorities and industry to meet the need for new clinical methods and a better environment. In addition, SciLifeLab provides education for students and researchers at all levels. SciLifeLab is hosted by four universities; Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University. The infrastructure is mainly located in Stockholm and Uppsala but we also offer services at other Swedish universities.

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